{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7d23aaec",
   "metadata": {},
   "source": [
    "# box plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7eeb33de",
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "\n",
    "plt.rcParams[\"axes.unicode_minus\"] = False\n",
    "plt.rcParams[\"font.sans-serif\"] = \"SimHei\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7841639e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.RandomState(42)\n",
    "data_box = np.random.randint(1,100,(100,4))\n",
    "data_box[1,1] = 200\n",
    "data_box[3,3] = -100\n",
    "label_box = ['A', 'B', 'C', 'D']\n",
    "fig, ax = plt.subplots(1,1, figsize=(3,3))\n",
    "ax.boxplot(data_box,label_box)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74021728",
   "metadata": {},
   "source": [
    "## dataframe supported"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "51fc36d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_box = pd.DataFrame(data=data_box, columns=label_box)\n",
    "fig, ax = plt.subplots(1,1, figsize=(3,3))\n",
    "ax.boxplot(df_box)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e353071c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "python3.6",
   "language": "python",
   "name": "python3.6"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
